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1 parent 734430d commit 16ff7a3
10 files changed
| Original file line number | Diff line number | Diff line change | |
|---|---|---|---|
@@ -276,8 +276,8 @@ public static float time() | |||
| 276 | 276 | { | |
| 277 | 277 | if (axis == null) | |
| 278 | 278 | { | |
| 279 | - var a = t1.Data<T>(); | ||
| 280 | - var b = t2.Data<T>(); | ||
| 279 | + var a = t1.ToArray<T>(); | ||
| 280 | + var b = t2.ToArray<T>(); | ||
| 281 | 281 | for (int i = 0; i < a.Length; i++) | |
| 282 | 282 | yield return (a[i], b[i]); | |
| 283 | 283 | } | |
| Original file line number | Diff line number | Diff line change | |
|---|---|---|---|
@@ -162,7 +162,7 @@ private NDArray DenseToOneHot(NDArray labels_dense, int num_classes) | |||
| 162 | 162 | var num_labels = labels_dense.dims[0]; | |
| 163 | 163 | var index_offset = np.arange(num_labels) * num_classes; | |
| 164 | 164 | var labels_one_hot = np.zeros((num_labels, num_classes)); | |
| 165 | - var labels = labels_dense.Data<byte>(); | ||
| 165 | + var labels = labels_dense.ToArray<byte>(); | ||
| 166 | 166 | for (int row = 0; row < num_labels; row++) | |
| 167 | 167 | { | |
| 168 | 168 | var col = labels[row]; | |
@@ -176,7 +176,7 @@ private int Read32(FileStream bytestream) | |||
| 176 | 176 | { | |
| 177 | 177 | var buffer = new byte[sizeof(uint)]; | |
| 178 | 178 | var count = bytestream.Read(buffer, 0, 4); | |
| 179 | - return np.frombuffer(buffer, ">u4").Data<int>()[0]; | ||
| 179 | + return np.frombuffer(buffer, ">u4").ToArray<int>()[0]; | ||
| 180 | 180 | } | |
| 181 | 181 | } | |
| 182 | 182 | } | |
| Original file line number | Diff line number | Diff line change | |
|---|---|---|---|
@@ -506,7 +506,7 @@ public static Tensor[] _SumGrad(Operation op, Tensor[] grads) | |||
| 506 | 506 | if (!(axes is null)) | |
| 507 | 507 | { | |
| 508 | 508 | var rank = input_0_shape.Length; | |
| 509 | - if (Enumerable.SequenceEqual(Enumerable.Range(0, rank), axes.Data<int>())) | ||
| 509 | + if (Enumerable.SequenceEqual(Enumerable.Range(0, rank), axes.ToArray<int>())) | ||
| 510 | 510 | { | |
| 511 | 511 | if (tf.Context.executing_eagerly()) | |
| 512 | 512 | { | |
| Original file line number | Diff line number | Diff line change | |
|---|---|---|---|
@@ -62,13 +62,9 @@ public NDIterator<T> AsIterator<T>(bool autoreset = false) where T : unmanaged | |||
| 62 | 62 | public byte[] ToByteArray() => _tensor.BufferToArray(); | |
| 63 | 63 | public static string[] AsStringArray(NDArray arr) => throw new NotImplementedException(""); | |
| 64 | 64 | ||
| 65 | - public T[] Data<T>() where T : unmanaged | ||
| 66 | - => _tensor.ToArray<T>(); | ||
| 67 | 65 | public T[] ToArray<T>() where T : unmanaged | |
| 68 | 66 | => _tensor.ToArray<T>(); | |
| 69 | 67 | ||
| 70 | - public static NDArray operator /(NDArray x, NDArray y) => throw new NotImplementedException(""); | ||
| 71 | - | ||
| 72 | 68 | public override string ToString() | |
| 73 | 69 | { | |
| 74 | 70 | return tensor_util.to_numpy_string(_tensor); | |
| Original file line number | Diff line number | Diff line change | |
|---|---|---|---|
@@ -257,7 +257,7 @@ bool hasattr(Graph property, string attr) | |||
| 257 | 257 | var dest_dtype_shape_array = np.array(x_).astype(cast_dtype.as_system_dtype()); | |
| 258 | 258 | ||
| 259 | 259 | long[] y_ = { }; | |
| 260 | - foreach (int y in dest_dtype_shape_array.Data<int>()) | ||
| 260 | + foreach (int y in dest_dtype_shape_array.ToArray<int>()) | ||
| 261 | 261 | if (y >= 0) | |
| 262 | 262 | y_[y_.Length] = y; | |
| 263 | 263 | else | |
| Original file line number | Diff line number | Diff line change | |
|---|---|---|---|
@@ -55,7 +55,7 @@ public NDArray pad_sequences(IEnumerable<int[]> sequences, | |||
| 55 | 55 | value = 0f; | |
| 56 | 56 | ||
| 57 | 57 | var type = dtypes.tf_dtype_from_name(dtype); | |
| 58 | - var nd = new NDArray((length.Count(), maxlen.Value), dtype: type); | ||
| 58 | + var nd = np.zeros((length.Count(), maxlen.Value), dtype: type); | ||
| 59 | 59 | ||
| 60 | 60 | for (int i = 0; i < nd.dims[0]; i++) | |
| 61 | 61 | { | |
| Original file line number | Diff line number | Diff line change | |
|---|---|---|---|
@@ -249,7 +249,7 @@ public void PadSequencesWithDefaults() | |||
| 249 | 249 | Assert.AreNotEqual(padded[1, i], 0); | |
| 250 | 250 | } | |
| 251 | 251 | ||
| 252 | - [TestMethod, Ignore("slice assign doesn't work")] | ||
| 252 | + [TestMethod] | ||
| 253 | 253 | public void PadSequencesPrePaddingTrunc() | |
| 254 | 254 | { | |
| 255 | 255 | var tokenizer = keras.preprocessing.text.Tokenizer(oov_token: OOV); | |
@@ -261,15 +261,15 @@ public void PadSequencesPrePaddingTrunc() | |||
| 261 | 261 | Assert.AreEqual(4, padded.dims[0]); | |
| 262 | 262 | Assert.AreEqual(15, padded.dims[1]); | |
| 263 | 263 | ||
| 264 | - Assert.AreEqual(tokenizer.word_index["worst"], padded[0, 12]); | ||
| 264 | + Assert.AreEqual(padded[0, 12], tokenizer.word_index["worst"]); | ||
| 265 | 265 | for (var i = 0; i < 3; i++) | |
| 266 | - Assert.AreEqual(0, padded[0, i]); | ||
| 267 | - Assert.AreEqual(tokenizer.word_index["proud"], padded[1, 3]); | ||
| 266 | + Assert.AreEqual(padded[0, i], 0); | ||
| 267 | + Assert.AreEqual(padded[1, 3], tokenizer.word_index["proud"]); | ||
| 268 | 268 | for (var i = 0; i < 15; i++) | |
| 269 | - Assert.AreNotEqual(0, padded[1, i]); | ||
| 269 | + Assert.AreNotEqual(padded[1, i], 0); | ||
| 270 | 270 | } | |
| 271 | 271 | ||
| 272 | - [TestMethod, Ignore("slice assign doesn't work")] | ||
| 272 | + [TestMethod] | ||
| 273 | 273 | public void PadSequencesPrePaddingTrunc_Larger() | |
| 274 | 274 | { | |
| 275 | 275 | var tokenizer = keras.preprocessing.text.Tokenizer(oov_token: OOV); | |
@@ -281,13 +281,13 @@ public void PadSequencesPrePaddingTrunc_Larger() | |||
| 281 | 281 | Assert.AreEqual(4, padded.dims[0]); | |
| 282 | 282 | Assert.AreEqual(45, padded.dims[1]); | |
| 283 | 283 | ||
| 284 | - Assert.AreEqual(tokenizer.word_index["worst"], padded[0, 42]); | ||
| 284 | + Assert.AreEqual(padded[0, 42], tokenizer.word_index["worst"]); | ||
| 285 | 285 | for (var i = 0; i < 33; i++) | |
| 286 | - Assert.AreEqual(0, padded[0, i]); | ||
| 287 | - Assert.AreEqual(tokenizer.word_index["proud"], padded[1, 33]); | ||
| 286 | + Assert.AreEqual(padded[0, i], 0); | ||
| 287 | + Assert.AreEqual(padded[1, 33], tokenizer.word_index["proud"]); | ||
| 288 | 288 | } | |
| 289 | 289 | ||
| 290 | - [TestMethod, Ignore("slice assign doesn't work")] | ||
| 290 | + [TestMethod] | ||
| 291 | 291 | public void PadSequencesPostPaddingTrunc() | |
| 292 | 292 | { | |
| 293 | 293 | var tokenizer = keras.preprocessing.text.Tokenizer(oov_token: OOV); | |
@@ -299,15 +299,15 @@ public void PadSequencesPostPaddingTrunc() | |||
| 299 | 299 | Assert.AreEqual(4, padded.dims[0]); | |
| 300 | 300 | Assert.AreEqual(15, padded.dims[1]); | |
| 301 | 301 | ||
| 302 | - Assert.AreEqual(tokenizer.word_index["worst"], padded[0, 9]); | ||
| 302 | + Assert.AreEqual(padded[0, 9], tokenizer.word_index["worst"]); | ||
| 303 | 303 | for (var i = 12; i < 15; i++) | |
| 304 | - Assert.AreEqual(0, padded[0, i]); | ||
| 305 | - Assert.AreEqual(tokenizer.word_index["proud"], padded[1, 10]); | ||
| 304 | + Assert.AreEqual(padded[0, i], 0); | ||
| 305 | + Assert.AreEqual(padded[1, 10], tokenizer.word_index["proud"]); | ||
| 306 | 306 | for (var i = 0; i < 15; i++) | |
| 307 | - Assert.AreNotEqual(0, padded[1, i]); | ||
| 307 | + Assert.AreNotEqual(padded[1, i], 0); | ||
| 308 | 308 | } | |
| 309 | 309 | ||
| 310 | - [TestMethod, Ignore("slice assign doesn't work")] | ||
| 310 | + [TestMethod] | ||
| 311 | 311 | public void PadSequencesPostPaddingTrunc_Larger() | |
| 312 | 312 | { | |
| 313 | 313 | var tokenizer = keras.preprocessing.text.Tokenizer(oov_token: OOV); | |
@@ -319,10 +319,10 @@ public void PadSequencesPostPaddingTrunc_Larger() | |||
| 319 | 319 | Assert.AreEqual(4, padded.dims[0]); | |
| 320 | 320 | Assert.AreEqual(45, padded.dims[1]); | |
| 321 | 321 | ||
| 322 | - Assert.AreEqual(tokenizer.word_index["worst"], padded[0, 9]); | ||
| 322 | + Assert.AreEqual(padded[0, 9], tokenizer.word_index["worst"]); | ||
| 323 | 323 | for (var i = 32; i < 45; i++) | |
| 324 | - Assert.AreEqual(0, padded[0, i]); | ||
| 325 | - Assert.AreEqual(tokenizer.word_index["proud"], padded[1, 10]); | ||
| 324 | + Assert.AreEqual(padded[0, i], 0); | ||
| 325 | + Assert.AreEqual(padded[1, 10], tokenizer.word_index["proud"]); | ||
| 326 | 326 | } | |
| 327 | 327 | ||
| 328 | 328 | [TestMethod] | |
| Original file line number | Diff line number | Diff line change | |
|---|---|---|---|
@@ -104,7 +104,7 @@ public void Tensor() | |||
| 104 | 104 | EXPECT_EQ(tensor.shape[0], nd.dims[0]); | |
| 105 | 105 | EXPECT_EQ(tensor.shape[1], nd.dims[1]); | |
| 106 | 106 | EXPECT_EQ(tensor.bytesize, nd.size * sizeof(float)); | |
| 107 | - Assert.IsTrue(Enumerable.SequenceEqual(nd.Data<float>(), new float[] { 1, 2, 3, 4, 5, 6 })); | ||
| 107 | + Assert.IsTrue(Enumerable.SequenceEqual(nd.ToArray<float>(), new float[] { 1, 2, 3, 4, 5, 6 })); | ||
| 108 | 108 | } | |
| 109 | 109 | ||
| 110 | 110 | /// <summary> | |
| Original file line number | Diff line number | Diff line change | |
|---|---|---|---|
@@ -26,43 +26,43 @@ public void empty_zeros_ones_full() | |||
| 26 | 26 | public void arange() | |
| 27 | 27 | { | |
| 28 | 28 | var x = np.arange(3); | |
| 29 | - AssetSequenceEqual(new[] { 0, 1, 2 }, x.Data<int>()); | ||
| 29 | + AssetSequenceEqual(new[] { 0, 1, 2 }, x.ToArray<int>()); | ||
| 30 | 30 | ||
| 31 | 31 | x = np.arange(3f); | |
| 32 | - Assert.IsTrue(Equal(new float[] { 0, 1, 2 }, x.Data<float>())); | ||
| 32 | + Assert.IsTrue(Equal(new float[] { 0, 1, 2 }, x.ToArray<float>())); | ||
| 33 | 33 | ||
| 34 | 34 | var y = np.arange(3, 7); | |
| 35 | - AssetSequenceEqual(new[] { 3, 4, 5, 6 }, y.Data<int>()); | ||
| 35 | + AssetSequenceEqual(new[] { 3, 4, 5, 6 }, y.ToArray<int>()); | ||
| 36 | 36 | ||
| 37 | 37 | y = np.arange(3, 7, 2); | |
| 38 | - AssetSequenceEqual(new[] { 3, 5 }, y.Data<int>()); | ||
| 38 | + AssetSequenceEqual(new[] { 3, 5 }, y.ToArray<int>()); | ||
| 39 | 39 | } | |
| 40 | 40 | ||
| 41 | 41 | [TestMethod] | |
| 42 | 42 | public void array() | |
| 43 | 43 | { | |
| 44 | 44 | var x = np.array(1, 2, 3); | |
| 45 | - AssetSequenceEqual(new[] { 1, 2, 3 }, x.Data<int>()); | ||
| 45 | + AssetSequenceEqual(new[] { 1, 2, 3 }, x.ToArray<int>()); | ||
| 46 | 46 | ||
| 47 | 47 | x = np.array(new[,] { { 1, 2 }, { 3, 4 }, { 5, 6 } }); | |
| 48 | - AssetSequenceEqual(new[] { 1, 2, 3, 4, 5, 6 }, x.Data<int>()); | ||
| 48 | + AssetSequenceEqual(new[] { 1, 2, 3, 4, 5, 6 }, x.ToArray<int>()); | ||
| 49 | 49 | } | |
| 50 | 50 | ||
| 51 | 51 | [TestMethod] | |
| 52 | 52 | public void eye() | |
| 53 | 53 | { | |
| 54 | 54 | var x = np.eye(3, k: 1); | |
| 55 | - Assert.IsTrue(Equal(new double[] { 0, 1, 0, 0, 0, 1, 0, 0, 0 }, x.Data<double>())); | ||
| 55 | + Assert.IsTrue(Equal(new double[] { 0, 1, 0, 0, 0, 1, 0, 0, 0 }, x.ToArray<double>())); | ||
| 56 | 56 | } | |
| 57 | 57 | ||
| 58 | 58 | [TestMethod] | |
| 59 | 59 | public void linspace() | |
| 60 | 60 | { | |
| 61 | 61 | var x = np.linspace(2.0, 3.0, num: 5); | |
| 62 | - Assert.IsTrue(Equal(new double[] { 2, 2.25, 2.5, 2.75, 3 }, x.Data<double>())); | ||
| 62 | + Assert.IsTrue(Equal(new double[] { 2, 2.25, 2.5, 2.75, 3 }, x.ToArray<double>())); | ||
| 63 | 63 | ||
| 64 | 64 | x = np.linspace(2.0, 3.0, num: 5, endpoint: false); | |
| 65 | - Assert.IsTrue(Equal(new double[] { 2, 2.2, 2.4, 2.6, 2.8 }, x.Data<double>())); | ||
| 65 | + Assert.IsTrue(Equal(new double[] { 2, 2.2, 2.4, 2.6, 2.8 }, x.ToArray<double>())); | ||
| 66 | 66 | } | |
| 67 | 67 | ||
| 68 | 68 | [TestMethod] | |
@@ -71,13 +71,13 @@ public void meshgrid() | |||
| 71 | 71 | var x = np.linspace(0, 1, num: 3); | |
| 72 | 72 | var y = np.linspace(0, 1, num: 2); | |
| 73 | 73 | var (xv, yv) = np.meshgrid(x, y); | |
| 74 | - Assert.IsTrue(Equal(new double[] { 0, 0.5, 1, 0, 0.5, 1 }, xv.Data<double>())); | ||
| 75 | - Assert.IsTrue(Equal(new double[] { 0, 0, 0, 1, 1, 1 }, yv.Data<double>())); | ||
| 74 | + Assert.IsTrue(Equal(new double[] { 0, 0.5, 1, 0, 0.5, 1 }, xv.ToArray<double>())); | ||
| 75 | + Assert.IsTrue(Equal(new double[] { 0, 0, 0, 1, 1, 1 }, yv.ToArray<double>())); | ||
| 76 | 76 | ||
| 77 | 77 | (xv, yv) = np.meshgrid(x, y, sparse: true); | |
| 78 | - Assert.IsTrue(Equal(new double[] { 0, 0.5, 1 }, xv.Data<double>())); | ||
| 78 | + Assert.IsTrue(Equal(new double[] { 0, 0.5, 1 }, xv.ToArray<double>())); | ||
| 79 | 79 | AssetSequenceEqual(new long[] { 1, 3 }, xv.shape.dims); | |
| 80 | - Assert.IsTrue(Equal(new double[] { 0, 1 }, yv.Data<double>())); | ||
| 80 | + Assert.IsTrue(Equal(new double[] { 0, 1 }, yv.ToArray<double>())); | ||
| 81 | 81 | AssetSequenceEqual(new long[] { 2, 1 }, yv.shape.dims); | |
| 82 | 82 | } | |
| 83 | 83 | } | |
| Original file line number | Diff line number | Diff line change | |
|---|---|---|---|
@@ -25,7 +25,7 @@ public void prod() | |||
| 25 | 25 | ||
| 26 | 26 | p = np.prod(new[,] { { 1.0, 2.0 }, { 3.0, 4.0 } }, axis: 1); | |
| 27 | 27 | Assert.AreEqual(p.shape, 2); | |
| 28 | - Assert.IsTrue(Equal(p.Data<double>(), new[] { 2.0, 12.0 })); | ||
| 28 | + Assert.IsTrue(Equal(p.ToArray<double>(), new[] { 2.0, 12.0 })); | ||
| 29 | 29 | } | |
| 30 | 30 | } | |
| 31 | 31 | } | |
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